I. Field of the Invention
This invention relates generally to a wide dynamic range digital receiver which is useful in the processing of sensor data, and more particularly to such a receiver exhibiting wide dynamic range in radar, sonar, communication, navigation and infrared systems.
II. Discussion of the Prior Art
Many systems employ sensors and filters to provide spatial discrimination and frequency discrimination against unwanted signals by linearly combining, in a very specific manner, the signals from a distributed array of sensors wherein each sensor in the array converts the received acoustic or electromagnetic signal into an electronic signal. Each sensor signal from the array is operated on in accordance with a specific mathematical formula such that a signal arriving from a specific direction relative to the orientation of the array of sensors is enhanced (amplified) and signals arriving from all other directions are suppressed. The operations on the sensor signal are performed in prior systems by analog electronic components, such as delay lines, phase shifters and summing amplifiers. Sensor signals are also operated on in accordance with a specific mathematical formula such that signals within a specific range of frequencies are enhanced (amplified) and signals outside the specific range of frequencies are suppressed. The filtering operations performed on the signals were implemented in prior systems with analog electronic components, such as capacitors, inductors, resistors and amplifiers. Analog components used to perform the operations required for spatial or frequency discrimination have the inherent problem that the components have a tolerance about their specified values and these values change with temperature and time, thereby making it impossible to implement the operations exactly as defined by the mathematics. The operations can be implemented exactly with no tolerances or variability with time or temperature using digital techniques.
The measure of performance in a receiver system is the accuracy to which a target can be localized, the sensitivity of the receiver to detect weak targets in the presence of environmental noise, and the dynamic range of the receiver, such that weak signals are not obscured by adjacent unwanted or interfering signals.
There exists a fairly well developed body of knowledge useful in predicting the theoretical limits of performance of receiver systems which also provides insight to the realization of near optimal performance. An example of this knowledge is contained in the text, Filtering in the Time and Frequency Domains, Blinchikoff and Zverev, John Wiley and Sons, 1976.
Early receiver systems were substantially analog in nature. All filtering functions were performed by hundreds of high precision circuit elements, resistors, inductors and capacitors. Later systems minimized the reliance on precision analog components by performing some of the filtering in the digital domain using specialized digital logic devices, e.g., digital multipliers, adders and digital shift registers. More recently, these functions have been accomplished using one or more stored program digital computers. A disadvantage of these digital techniques is that the receiver dynamic range is less than the dynamic range of an equivalent receiver implemented with analog components.
Digital signal processing has yielded a number of very important benefits. First, the process can be scaled to any frequency regime. Second, the processing errors can be reduced to very small deterministic values by choosing an appropriate size digital word, i.e., the error decreases as the length or precision of the digital word is increased.
Digital signal processing requires that each analog sensor signal be converted to a digital representation. In this process, the analog signal is sampled at a regular time interval, .DELTA.t, by an analog-to-digital converter (ADC) which converts the magnitude and polarity to a binary numerical representation. The signal is thus quantized in amplitude at regular intervals. The quantization process imposes new constraints upon the performance of the system. A critical requirement is that the sampling frequency must be at least twice the bandwidth of the signal of interest. This requirement is generally known as the Nyquist criteria. If this criteria is not met, error is introduced through the phenomenon of aliasing in which signal components outside the band of interest are superimposed on the signals within the band of interest.
Another constraint on the system is the reduction of dynamic range due to quantization noise introduced by the ADC. The dynamic range is defined as the ratio between the maximum input signal to the quantization noise density (i.e., noise power in a 1 Hz bandwidth). The maximum input signal, Sm, is scaled to correspond to the maximum linear input voltage to the ADC, typically 10 volts. The quantization interval of the ADC is determined by the weighting of the least significant bit of the ADC and is thus equal to Sm divided by 2.sup.n-1, where n is the number of bits in the ADC output. Quantization noise arises out of the difference between the actual value of the input signal sample and the quantized value at each sample and varies uniformly over the quantization interval. For an ADC with uniform quantization intervals, q, the quantization error probability density function is given by ##STR1## The quantization error noise power is given by ##EQU1##
The quantization error noise power is uniformly spread in frequency from 0 to 1/2 the sampling frequency, FS. The quantization noise density Q.sub.n, i.e., the RMS value of the quantization noise in a one hertz bandwidth, is thus a function of both the quantization interval and the sample frequency and is given by the equation: EQU Qn=20 log [2Sm/(2.sup.n -1)(.sqroot.12)]-10 log (FS/2) EQ.1
Then, the dynamic range, DR, can be expressed as: EQU DR=20 log Sm-20 log [Sm/(2.sup.n -1)(.sqroot.12)]+10 log (FS/2)]=20 log [2.sup.n -1)/(.sqroot.12)]+10 log (FS/2)-6 dB EQ.2
It can thus be seen from equation 2 that the DR of the ADC (or receiver) increases as the sample frequency, FS, is increased for a fixed binary word size out of the ADC. The present invention makes use of this relationship.